DopeyBadger
Imagathoner
- Joined
- Oct 15, 2015
- Messages
- 10,345
Alright readers (posters and lurkers alike), I've got a question for you! 
My coworker and I were discussing Boston Qualifying Times today. She was excited to turn 45 soon and increase her BQ time to 3:55. I am at 3:05 for the next few years until I'm 35 on race day. She stated that it was rough for me to have a BQ of 3:05 because that's so fast. And I posed that since BQs are age and gender specific, was my time of 3:05 really that different than her 3:55? Whose time was harder to accomplish given our age/gender?
So, I did the following. I used the BQ times as of right now and looked at the 2014 Chicago Marathon results. I figured out how many people in each division ran a BQ time, and then divided it by the total number of people in each division. Thus, it gave me a percentage of BQ qualifying times per division. So the graph and the data....
x-axis equals age
y-axis equals % of finish times that were BQ
blue bar is male
pink bar is female
lines represent merely the BQ times required and location on graph has zero correlation to the height of the bars
So the question to you is two-fold:
1) What do you interpret from this data?
2) If I were to use a different marathon (say 2014 Grandma's marathon) based on your conclusions in question 1, what would you anticipate would be the same in the Grandma results? And what would you anticipate could be different?
I have my ideas, but I want to see whether any of you would like to share yours first. Set GO!

My coworker and I were discussing Boston Qualifying Times today. She was excited to turn 45 soon and increase her BQ time to 3:55. I am at 3:05 for the next few years until I'm 35 on race day. She stated that it was rough for me to have a BQ of 3:05 because that's so fast. And I posed that since BQs are age and gender specific, was my time of 3:05 really that different than her 3:55? Whose time was harder to accomplish given our age/gender?
So, I did the following. I used the BQ times as of right now and looked at the 2014 Chicago Marathon results. I figured out how many people in each division ran a BQ time, and then divided it by the total number of people in each division. Thus, it gave me a percentage of BQ qualifying times per division. So the graph and the data....

x-axis equals age
y-axis equals % of finish times that were BQ
blue bar is male
pink bar is female
lines represent merely the BQ times required and location on graph has zero correlation to the height of the bars

So the question to you is two-fold:
1) What do you interpret from this data?
2) If I were to use a different marathon (say 2014 Grandma's marathon) based on your conclusions in question 1, what would you anticipate would be the same in the Grandma results? And what would you anticipate could be different?
I have my ideas, but I want to see whether any of you would like to share yours first. Set GO!
